Managed historians utilize cloud computing environments to provide a multi-tenant software-as-a-service solution for storing and enabling access to historical data, such as time-series data for example, relating to continuous processes and their associated outputs. When the historical data is displayed on a display device (e.g., as a line chart, etc.), the data values at a particular time may visually differ from the data values at other times. For example, the visual difference may be a spike, a rate, and the like. Understanding the specific reasons for the value differences helps optimize operation of the continuous process. For example, the reason may be an event such as line downtime, a production status change, a product change, a crew change, and the like. Conventional techniques prepend a historian name to process tags that represent the data values and stamp events with a globally unique identifier (GUID) of the event data source. These techniques enable searching for tags and events but fail to provide any linkage between changes in process data values and the associated events responsible for the changes.